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Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for highthroughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues.

The centromeric histone H3 variant cenH3 is an essential centromeric protein required for assembly, maintenance, and proper function of kinetochores during mitosis and meiosis. We identified a KINETOCHORE NULL2 (KNL2) homolog in Arabidopsis thaliana and uncovered features of its role in cenH3 loading at centromeres. We show that Arabidopsis KNL2 colocalizes with cenH3 and is associated with centromeres during all stages of the mitotic cell cycle, except from metaphase to mid-anaphase. KNL2 is regulated by the proteasome degradation pathway. The KNL2 promoter is mainly active in meristematic tissues, similar to the cenH3 promoter. A knockout mutant for KNL2 shows a reduced level of cenH3 expression and reduced amount of cenH3 protein at chromocenters of meristematic nuclei, anaphase bridges during mitosis, micronuclei in pollen tetrads, and 30% seed abortion. Moreover, knl2 mutant plants display reduced expression of suppressor of variegation 3-9 homologs2, 4, and 9 and reduced DNA methylation, suggesting an impact of KNL2 on the epigenetic environment for centromere maintenance.

SUMMARYHeterosis-associated cellular and molecular processes were analyzed in seeds and seedlings of Arabidopsis thaliana accessions Col-0 and C24 and their heterotic hybrids. Microscopic examination revealed no advantages in terms of hybrid mature embryo organ sizes or cell numbers. Increased cotyledon sizes were detectable 4 days after sowing. Growth heterosis results from elevated cell sizes and numbers, and is well established at 10 days after sowing. The relative growth rates of hybrid seedlings were most enhanced between 3 and 4 days after sowing. Global metabolite profiling and targeted fatty acid analysis revealed maternal inheritance patterns for a large proportion of metabolites in the very early stages. During developmental progression, the distribution shifts to dominant, intermediate and heterotic patterns, with most changes occurring between 4 and 6 days after sowing. The highest incidence of heterotic patterns coincides with establishment of size differences at 4 days after sowing. In contrast, overall transcript patterns at 4, 6 and 10 days after sowing are characterized by intermediate to dominant patterns, with parental transcript levels showing the largest differences. Overall, the results suggest that, during early developmental stages, intermediate gene expression and higher metabolic activity in the hybrids compared to the parents lead to better resource efficiency, and therefore enhanced performance in the hybrids.

SUMMARYBarley endosperm cells differentiate into transfer cells (ETCs) opposite the nucellar projection. To comprehensively analyse ETC differentiation, laser microdissection-based transcript and metabolite profiles were obtained from laser microdissected tissues and cell morphology was analysed. Flange-like secondary-wall ingrowths appeared between 5 and 7 days after pollination within the three outermost cell layers. Gene expression analysis indicated that ethylene-signalling pathways initiate ETC morphology. This is accompanied by gene activity related to cell shape control and vesicle transport, with abundant mitochondria and endomembrane structures. Gene expression analyses indicate predominant formation of hemicelluloses, glucuronoxylans and arabinoxylans, and transient formation of callose, together with proline and 4-hydroxyproline biosynthesis. Activation of the methylation cycle is probably required for biosynthesis of phospholipids, pectins and ethylene. Membrane microdomains involving sterols/sphingolipids and remorins are potentially involved in ETC development. The transcriptional activity of assimilate and micronutrient transporters suggests ETCs as the main uptake organs of solutes into the endosperm. Accordingly, the endosperm grows maximally after ETCs are fully developed. Up-regulated gene expression related to amino acid catabolism, C:N balances, carbohydrate oxidation, mitochondrial activity and starch degradation meets high demands for respiratory energy and carbohydrates, required for cell proliferation and wall synthesis. At 10 days after pollination, ETCs undergo further differentiation, potentially initiated by abscisic acid, and metabolism is reprogrammed as shown by activated storage and stress-related processes. Overall, the data provide a comprehensive view of barley ETC differentiation and development, and identify candidate genes and associated pathways.

Phenotyping large numbers of genotypes still represents the rate-limiting step in many plant genetic experiments and in breeding. To address this issue, novel automated phenotyping technologies have been developed. We investigated for a core set of barley cultivars if high-throughput image analysis can help to dissect vegetative biomass accumulation in response to two different watering regimes under semi-controlled greenhouse conditions. We found that experiments, treatments, genotypes and genotype by environment interaction (G × E) can be characterized at any time point by certain digital traits. Biomass accumulation under control and stress conditions was highly heritable. Growth model-derived maximum vegetative biomass (K max), inflection point (I) and regrowth rate (k) were identified as promising candidate traits for genome-wide association studies. Drought stress symptoms can be visualized, dissected and modelled. Especially the highly heritable regrowth rate, which had the biggest influence on biomass accumulation in stress treatment, seems promising for future studies to improve drought tolerance in different crop species. A proof of concept study revealed potential correlations between digital traits obtained from pot experiments under greenhouse conditions and agronomic traits from field experiments. Overall, non-invasive, imaging-based phenotyping platforms under greenhouse conditions offer excellent possibilities for trait discovery, trait development and industrial applications.

BackgroundSeed metabolism is dynamically adjusted to oxygen availability. Processes underlying this auto-regulatory mechanism control the metabolic efficiency under changing environmental conditions/stress and thus, are of relevance for biotechnology. Non-symbiotic hemoglobins have been shown to be involved in scavenging of nitric oxide (NO) molecules, which play a key role in oxygen sensing/balancing in plants and animals. Steady state levels of NO are suggested to act as an integrator of energy and carbon metabolism and subsequently, influence energy-demanding growth processes in plants.ResultsWe aimed to manipulate oxygen stress perception in Arabidopsis seeds by overexpression of the non-symbiotic hemoglobin AtHb1 under the control of the seed-specific LeB4 promoter. Seeds of transgenic AtHb1 plants did not accumulate NO under transient hypoxic stress treatment, showed higher respiratory activity and energy status compared to the wild type. Global transcript profiling of seeds/siliques from wild type and transgenic plants under transient hypoxic and standard conditions using Affymetrix ATH1 chips revealed a rearrangement of transcriptional networks by AtHb1 overexpression under non-stress conditions, which included the induction of transcripts related to ABA synthesis and signaling, receptor-like kinase- and MAP kinase-mediated signaling pathways, WRKY transcription factors and ROS metabolism. Overexpression of AtHb1 shifted seed metabolism to an energy-saving mode with the most prominent alterations occurring in cell wall metabolism. In combination with metabolite and physiological measurements, these data demonstrate that AtHb1 overexpression improves oxidative stress tolerance compared to the wild type where a strong transcriptional and metabolic reconfiguration was observed in the hypoxic response.ConclusionsAtHb1 overexpression mediates a pre-adaptation to hypoxic stress. Under transient stress conditions transgenic seeds were able to keep low levels of endogenous NO and to maintain a high energy status, in contrast to wild type. Higher weight of mature transgenic seeds demonstrated the beneficial effects of seed-specific overexpression of AtHb1.

The need for higher yielding and better-adapted crop plants for feeding the world's rapidly growing population has raised the question of how to systematically utilize large genebank collections with their wide range of largely untouched genetic diversity. Phenotypic data that has been recorded for decades during various rounds of seed multiplication provides a rich source of information. Their usefulness has remained limited though, due to various biases induced by conservation management over time or changing environmental conditions. Here, we present a powerful procedure that permits an unbiased trait-based selection of plant samples based on such phenotypic data. Applying this technique to the wheat collection of one of the largest genebanks worldwide, we identified groups of plant samples displaying contrasting phenotypes for selected traits. As a proof of concept for our discovery pipeline, we resequenced the entire major but conserved flowering time locus Ppd-D1 in just a few such selected wheat samples – and nearly doubled the number of hitherto known alleles.